def _insert_preprocessed_data(study, params, prep_template, slq_out,
**kwargs):
"""Inserts the preprocessed data to the database
Parameters
----------
study : Study
The study to preprocess
params : BaseParameters
The parameters to use for preprocessing
prep_template : PrepTemplate
The prep template to use for the preprocessing
slq_out : str
Path to the split_libraries_fastq.py output directory
kwargs: ignored
Necessary to include to support execution via moi.
Raises
------
ValueError
If the preprocessed output directory does not contain all the expected
files
"""
from os.path import exists, join
from functools import partial
from qiita_db.data import PreprocessedData
# The filepaths that we are interested in are:
# 1) seqs.fna -> demultiplexed fasta file
# 2) seqs.fastq -> demultiplexed fastq file
# 3) seqs.demux -> demultiplexed HDF5 file
path_builder = partial(join, slq_out)
fasta_fp = path_builder('seqs.fna')
fastq_fp = path_builder('seqs.fastq')
demux_fp = path_builder('seqs.demux')
log_fp = path_builder('split_library_log.txt')
# Check that all the files exist
if not (exists(fasta_fp) and exists(demux_fp) and exists(log_fp)):
raise ValueError("The output directory %s does not contain all the "
"expected files." % slq_out)
filepaths = [(fasta_fp, "preprocessed_fasta"),
(demux_fp, "preprocessed_demux"),
(log_fp, "log")]
if exists(fastq_fp):
filepaths.append((fastq_fp, "preprocessed_fastq"))
PreprocessedData.create(study, params._table, params.id, filepaths,
prep_template)
# Change the prep_template status to success
prep_template.preprocessing_status = 'success'
def _insert_preprocessed_data(study, params, prep_template, slq_out, **kwargs):
"""Inserts the preprocessed data to the database
Parameters
----------
study : Study
The study to preprocess
params : BaseParameters
The parameters to use for preprocessing
prep_template : PrepTemplate
The prep template to use for the preprocessing
slq_out : str
Path to the split_libraries_fastq.py output directory
kwargs: ignored
Necessary to include to support execution via moi.
Raises
------
ValueError
If the preprocessed output directory does not contain all the expected
files
"""
from os.path import exists, join
from functools import partial
from qiita_db.data import PreprocessedData
# The filepaths that we are interested in are:
# 1) seqs.fna -> demultiplexed fasta file
# 2) seqs.fastq -> demultiplexed fastq file
# 3) seqs.demux -> demultiplexed HDF5 file
path_builder = partial(join, slq_out)
fasta_fp = path_builder('seqs.fna')
fastq_fp = path_builder('seqs.fastq')
demux_fp = path_builder('seqs.demux')
log_fp = path_builder('split_library_log.txt')
# Check that all the files exist
if not (exists(fasta_fp) and exists(demux_fp) and exists(log_fp)):
raise ValueError("The output directory %s does not contain all the "
"expected files." % slq_out)
filepaths = [(fasta_fp, "preprocessed_fasta"),
(demux_fp, "preprocessed_demux"), (log_fp, "log")]
if exists(fastq_fp):
filepaths.append((fastq_fp, "preprocessed_fastq"))
PreprocessedData.create(study, params._table, params.id, filepaths,
prep_template)
# Change the prep_template status to success
prep_template.preprocessing_status = 'success'
def test_create_error_data_type(self):
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study,
"preprocessed_sequence_illumina_params",
self.params_id, self.filepaths,
data_type="Metabolomics")
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study,
"preprocessed_sequence_illumina_params",
self.params_id, self.filepaths,
data_type="Metabolomics",
prep_template=self.prep_template)
def test_create_error_data_type(self):
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study,
"preprocessed_sequence_illumina_params",
self.params_id, self.filepaths,
data_type="Metabolomics")
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study,
"preprocessed_sequence_illumina_params",
self.params_id, self.filepaths,
data_type="Metabolomics",
prep_template=self.prep_template)
def test_create_error_dynamic_table(self):
"""Raises an error if the preprocessed_params_table does not exist"""
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study,
"foo",
self.params_id,
self.filepaths,
data_type="18S")
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study,
"preprocessed_foo",
self.params_id,
self.filepaths,
data_type="18S")
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study,
"foo_params",
self.params_id,
self.filepaths,
data_type="18S")
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study,
"preprocessed_foo_params",
self.params_id,
self.filepaths,
data_type="18S")
def test_processing_status_setter_valueerror(self):
"""Raises an error if the processing status is not recognized"""
ppd = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="18S")
with self.assertRaises(ValueError):
ppd.processing_status = 'not a valid state'
def test_processing_status_setter_valueerror(self):
"""Raises an error if the processing status is not recognized"""
ppd = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="18S")
with self.assertRaises(ValueError):
ppd.processing_status = 'not a valid state'
def test_create_data_type_only(self):
# Check that the returned object has the correct id
obs = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="18S")
self.assertEqual(obs.id, 3)
# Check that the preprocessed data have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_data WHERE "
"preprocessed_data_id=3")
# preprocessed_data_id, preprocessed_params_table,
# preprocessed_params_id, submitted_to_insdc_status,
# ebi_submission_accession, ebi_study_accession, data_type_id,
# link_filepaths_status, vamps_status, processing_status
exp = [[3, "preprocessed_sequence_illumina_params", 1,
'not submitted', None, None, 2, 'idle', 'not submitted',
'not_processed']]
self.assertEqual(obs, exp)
# Check that the preprocessed data has been linked with its study
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.study_preprocessed_data WHERE "
"preprocessed_data_id=3")
exp = [[1, 3]]
self.assertEqual(obs, exp)
# Check that the files have been copied to right location
exp_fna_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.fna_fp))
self.assertTrue(exists(exp_fna_fp))
self._clean_up_files.append(exp_fna_fp)
exp_qual_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.qual_fp))
self.assertTrue(exists(exp_qual_fp))
self._clean_up_files.append(exp_qual_fp)
# Check that the filepaths have been correctly added to the DB
obs_id = self.conn_handler.execute_fetchone(
"SELECT count(1) from qiita.filepath")[0]
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.filepath WHERE filepath_id=%d or "
"filepath_id=%d" % (obs_id - 1, obs_id))
exp_fna_fp = "3_%s" % basename(self.fna_fp)
exp_qual_fp = "3_%s" % basename(self.qual_fp)
# filepath_id, path, filepath_type_id
exp = [[obs_id - 1, exp_fna_fp, 4, '852952723', 1, 3],
[obs_id, exp_qual_fp, 5, '852952723', 1, 3]]
self.assertEqual(obs, exp)
# Check that the preprocessed data have been correctly
# linked with the filepaths
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_filepath WHERE "
"preprocessed_data_id=3")
# preprocessed_data_id, filepath_id
self.assertEqual(obs, [[3, obs_id - 1], [3, obs_id]])
def test_create_data_type_only(self):
# Check that the returned object has the correct id
obs = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="18S")
self.assertEqual(obs.id, 3)
# Check that the preprocessed data have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_data WHERE "
"preprocessed_data_id=3")
# preprocessed_data_id, preprocessed_params_table,
# preprocessed_params_id, submitted_to_insdc_status,
# ebi_submission_accession, ebi_study_accession, data_type_id,
# link_filepaths_status, vamps_status, processing_status
exp = [[3, "preprocessed_sequence_illumina_params", 1,
'not submitted', None, None, 2, 'idle', 'not submitted',
'not_processed']]
self.assertEqual(obs, exp)
# Check that the preprocessed data has been linked with its study
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.study_preprocessed_data WHERE "
"preprocessed_data_id=3")
exp = [[1, 3]]
self.assertEqual(obs, exp)
# Check that the files have been copied to right location
exp_fna_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.fna_fp))
self.assertTrue(exists(exp_fna_fp))
self._clean_up_files.append(exp_fna_fp)
exp_qual_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.qual_fp))
self.assertTrue(exists(exp_qual_fp))
self._clean_up_files.append(exp_qual_fp)
# Check that the filepaths have been correctly added to the DB
obs_id = self.conn_handler.execute_fetchone(
"SELECT count(1) from qiita.filepath")[0]
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.filepath WHERE filepath_id=%d or "
"filepath_id=%d" % (obs_id - 1, obs_id))
exp_fna_fp = "3_%s" % basename(self.fna_fp)
exp_qual_fp = "3_%s" % basename(self.qual_fp)
# filepath_id, path, filepath_type_id
exp = [[obs_id - 1, exp_fna_fp, 4, '852952723', 1, 3],
[obs_id, exp_qual_fp, 5, '852952723', 1, 3]]
self.assertEqual(obs, exp)
# Check that the preprocessed data have been correctly
# linked with the filepaths
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_filepath WHERE "
"preprocessed_data_id=3")
# preprocessed_data_id, filepath_id
self.assertEqual(obs, [[3, obs_id - 1], [3, obs_id]])
def test_ebi_study_accession(self):
new = PreprocessedData.create(
self.study, self.params_table,
self.params_id, self.filepaths, prep_template=self.prep_template,
ebi_submission_accession=self.ebi_submission_accession,
ebi_study_accession=self.ebi_study_accession)
new.ebi_study_accession = 'EBI12345-DD'
self.assertEqual(new.ebi_study_accession, 'EBI12345-DD')
def test_set_ebi_submission_accession(self):
new = PreprocessedData.create(
self.study, self.params_table, self.params_id, self.filepaths,
raw_data=self.raw_data,
ebi_submission_accession=self.ebi_submission_accession,
ebi_study_accession=self.ebi_study_accession)
new.ebi_submission_accession = 'EBI12345-CC'
self.assertEqual(new.ebi_submission_accession, 'EBI12345-CC')
def test_ebi_study_accession(self):
new = PreprocessedData.create(
self.study, self.params_table,
self.params_id, self.filepaths, prep_template=self.prep_template,
ebi_submission_accession=self.ebi_submission_accession,
ebi_study_accession=self.ebi_study_accession)
new.ebi_study_accession = 'EBI12345-DD'
self.assertEqual(new.ebi_study_accession, 'EBI12345-DD')
def test_processing_status(self):
"""processing_status works correctly"""
# Processed case
ppd = PreprocessedData(1)
self.assertEqual(ppd.processing_status, 'not_processed')
# not processed case
ppd = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="18S")
self.assertEqual(ppd.processing_status, 'not_processed')
def test_processing_status(self):
"""processing_status works correctly"""
# Processed case
ppd = PreprocessedData(1)
self.assertEqual(ppd.processing_status, 'not_processed')
# not processed case
ppd = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="18S")
self.assertEqual(ppd.processing_status, 'not_processed')
def test_insert_processed_data_target_gene(self):
fd, fna_fp = mkstemp(suffix='_seqs.fna')
close(fd)
fd, qual_fp = mkstemp(suffix='_seqs.qual')
close(fd)
filepaths = [
(fna_fp, convert_to_id('preprocessed_fasta', 'filepath_type')),
(qual_fp, convert_to_id('preprocessed_fastq', 'filepath_type'))
]
preprocessed_data = PreprocessedData.create(
Study(1),
"preprocessed_sequence_illumina_params",
1,
filepaths,
data_type="18S")
params = ProcessedSortmernaParams(1)
pick_dir = mkdtemp()
path_builder = partial(join, pick_dir)
db_path_builder = partial(join, get_mountpoint('processed_data')[0][1])
# Create a placeholder for the otu table
with open(path_builder('otu_table.biom'), 'w') as f:
f.write('\n')
# Create a placeholder for the directory
mkdir(path_builder('sortmerna_picked_otus'))
# Create the log file
fd, fp = mkstemp(dir=pick_dir, prefix='log_', suffix='.txt')
close(fd)
with open(fp, 'w') as f:
f.write('\n')
_insert_processed_data_target_gene(preprocessed_data, params, pick_dir)
new_id = get_count('qiita.processed_data')
# Check that the files have been copied
db_files = [
db_path_builder("%s_otu_table.biom" % new_id),
db_path_builder("%s_sortmerna_picked_otus" % new_id),
db_path_builder("%s_%s" % (new_id, basename(fp)))
]
for fp in db_files:
self.assertTrue(exists(fp))
# Check that a new preprocessed data has been created
self.assertTrue(
self.conn_handler.execute_fetchone(
"SELECT EXISTS(SELECT * FROM qiita.processed_data WHERE "
"processed_data_id=%s)", (new_id, ))[0])
def test_set_ebi_submission_accession(self):
new = PreprocessedData.create(
self.study,
self.params_table,
self.params_id,
self.filepaths,
raw_data=self.raw_data,
ebi_submission_accession=self.ebi_submission_accession,
ebi_study_accession=self.ebi_study_accession)
new.ebi_submission_accession = 'EBI12345-CC'
self.assertEqual(new.ebi_submission_accession, 'EBI12345-CC')
def test_create_error(self):
"""Raises an error if the preprocessed_params_table does not exist"""
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study, "foo", self.params_id,
self.filepaths)
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study, "preprocessed_foo",
self.params_id, self.filepaths)
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study, "foo_params", self.params_id,
self.filepaths)
with self.assertRaises(IncompetentQiitaDeveloperError):
PreprocessedData.create(self.study, "preprocessed_foo_params",
self.params_id, self.filepaths)
def test_processing_status_setter(self):
"""Able to update the processing status"""
ppd = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="18S")
self.assertEqual(ppd.processing_status, 'not_processed')
ppd.processing_status = 'processing'
self.assertEqual(ppd.processing_status, 'processing')
ppd.processing_status = 'processed'
self.assertEqual(ppd.processing_status, 'processed')
state = 'failed: some error message'
ppd.processing_status = state
self.assertEqual(ppd.processing_status, state)
def test_processing_status_setter(self):
"""Able to update the processing status"""
ppd = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="18S")
self.assertEqual(ppd.processing_status, 'not_processed')
ppd.processing_status = 'processing'
self.assertEqual(ppd.processing_status, 'processing')
ppd.processing_status = 'processed'
self.assertEqual(ppd.processing_status, 'processed')
state = 'failed: some error message'
ppd.processing_status = state
self.assertEqual(ppd.processing_status, state)
def test_create(self):
"""Correctly creates all the rows in the DB for preprocessed data"""
# Check that the returned object has the correct id
obs = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
raw_data=self.raw_data)
self.assertEqual(obs.id, 3)
# Check that the preprocessed data have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_data WHERE "
"preprocessed_data_id=3")
# preprocessed_data_id, raw_data_id, preprocessed_params_tables,
# preprocessed_params_id
exp = [[3, "preprocessed_sequence_illumina_params", 1, False]]
self.assertEqual(obs, exp)
# Check that the preprocessed data has been linked with its study
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.study_preprocessed_data WHERE "
"preprocessed_data_id=3")
exp = [[1, 3]]
self.assertEqual(obs, exp)
# Check that the files have been copied to right location
exp_fna_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.fna_fp))
self.assertTrue(exists(exp_fna_fp))
self._clean_up_files.append(exp_fna_fp)
exp_qual_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.qual_fp))
self.assertTrue(exists(exp_qual_fp))
self._clean_up_files.append(exp_qual_fp)
# Check that the filepaths have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.filepath WHERE filepath_id=10 or "
"filepath_id=11")
# filepath_id, path, filepath_type_id
exp = [[10, exp_fna_fp, 4, '852952723', 1],
[11, exp_qual_fp, 5, '852952723', 1]]
self.assertEqual(obs, exp)
# Check that the preprocessed data have been correctly
# linked with the filepaths
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_filepath WHERE "
"preprocessed_data_id=3")
# preprocessed_data_id, filepath_id
self.assertEqual(obs, [[3, 10], [3, 11]])
def test_create(self):
"""Correctly creates all the rows in the DB for preprocessed data"""
# Check that the returned object has the correct id
obs = PreprocessedData.create(
self.study, self.params_table,
self.params_id, self.filepaths, prep_template=self.prep_template,
ebi_submission_accession=self.ebi_submission_accession,
ebi_study_accession=self.ebi_study_accession)
self.assertEqual(obs.id, 3)
# Check that the preprocessed data have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_data WHERE "
"preprocessed_data_id=3")
# preprocessed_data_id, preprocessed_params_table,
# preprocessed_params_id, submitted_to_insdc_status,
# ebi_submission_accession, ebi_study_accession, data_type_id,
# link_filepaths_status, vamps_status, processing_status
exp = [[3, "preprocessed_sequence_illumina_params", 1,
'not submitted', "EBI123456-A", "EBI123456-B", 2, 'idle',
'not submitted', 'not_processed']]
self.assertEqual(obs, exp)
# Check that the preprocessed data has been linked with its study
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.study_preprocessed_data WHERE "
"preprocessed_data_id=3")
exp = [[1, 3]]
self.assertEqual(obs, exp)
# Check that the files have been copied to right location
exp_fna_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.fna_fp))
self.assertTrue(exists(exp_fna_fp))
self._clean_up_files.append(exp_fna_fp)
exp_qual_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.qual_fp))
self.assertTrue(exists(exp_qual_fp))
self._clean_up_files.append(exp_qual_fp)
# Check that the filepaths have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.filepath WHERE filepath_id=17 or "
"filepath_id=18")
exp_fna_fp = "3_%s" % basename(self.fna_fp)
exp_qual_fp = "3_%s" % basename(self.qual_fp)
# filepath_id, path, filepath_type_id
exp = [[17, exp_fna_fp, 4, '852952723', 1, 3],
[18, exp_qual_fp, 5, '852952723', 1, 3]]
self.assertEqual(obs, exp)
def test_create_data_type_only(self):
# Check that the returned object has the correct id
obs = PreprocessedData.create(self.study,
self.params_table,
self.params_id,
self.filepaths,
data_type="18S")
self.assertEqual(obs.id, 3)
# Check that the preprocessed data have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_data WHERE "
"preprocessed_data_id=3")
exp = [[
3, "preprocessed_sequence_illumina_params", 1, False, None, None, 2
]]
self.assertEqual(obs, exp)
# Check that the preprocessed data has been linked with its study
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.study_preprocessed_data WHERE "
"preprocessed_data_id=3")
exp = [[1, 3]]
self.assertEqual(obs, exp)
# Check that the files have been copied to right location
exp_fna_fp = join(self.db_test_ppd_dir, "3_%s" % basename(self.fna_fp))
self.assertTrue(exists(exp_fna_fp))
self._clean_up_files.append(exp_fna_fp)
exp_qual_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.qual_fp))
self.assertTrue(exists(exp_qual_fp))
self._clean_up_files.append(exp_qual_fp)
# Check that the filepaths have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.filepath WHERE filepath_id=15 or "
"filepath_id=16")
# filepath_id, path, filepath_type_id
exp = [[15, exp_fna_fp, 4, '852952723', 1],
[16, exp_qual_fp, 5, '852952723', 1]]
self.assertEqual(obs, exp)
# Check that the preprocessed data have been correctly
# linked with the filepaths
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_filepath WHERE "
"preprocessed_data_id=3")
# preprocessed_data_id, filepath_id
self.assertEqual(obs, [[3, 15], [3, 16]])
def test_create(self):
"""Correctly creates all the rows in the DB for preprocessed data"""
# Check that the returned object has the correct id
obs = PreprocessedData.create(
self.study,
self.params_table,
self.params_id,
self.filepaths,
raw_data=self.raw_data,
ebi_submission_accession=self.ebi_submission_accession,
ebi_study_accession=self.ebi_study_accession)
self.assertEqual(obs.id, 3)
# Check that the preprocessed data have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.preprocessed_data WHERE "
"preprocessed_data_id=3")
exp = [[
3, "preprocessed_sequence_illumina_params", 1, False,
"EBI123456-A", "EBI123456-B", 2
]]
self.assertEqual(obs, exp)
# Check that the preprocessed data has been linked with its study
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.study_preprocessed_data WHERE "
"preprocessed_data_id=3")
exp = [[1, 3]]
self.assertEqual(obs, exp)
# Check that the files have been copied to right location
exp_fna_fp = join(self.db_test_ppd_dir, "3_%s" % basename(self.fna_fp))
self.assertTrue(exists(exp_fna_fp))
self._clean_up_files.append(exp_fna_fp)
exp_qual_fp = join(self.db_test_ppd_dir,
"3_%s" % basename(self.qual_fp))
self.assertTrue(exists(exp_qual_fp))
self._clean_up_files.append(exp_qual_fp)
# Check that the filepaths have been correctly added to the DB
obs = self.conn_handler.execute_fetchall(
"SELECT * FROM qiita.filepath WHERE filepath_id=15 or "
"filepath_id=16")
# filepath_id, path, filepath_type_id
exp = [[15, exp_fna_fp, 4, '852952723', 1],
[16, exp_qual_fp, 5, '852952723', 1]]
self.assertEqual(obs, exp)
def test_delete_advanced(self):
# testing that we can not remove cause preprocessed data has been
# submitted to EBI or VAMPS
ppd = PreprocessedData.create(
self.study, self.params_table,
self.params_id, self.filepaths, prep_template=self.prep_template)
# fails due to VAMPS submission
ppd.update_vamps_status('success')
with self.assertRaises(QiitaDBStatusError):
PreprocessedData.delete(ppd.id)
ppd.update_vamps_status('failed')
ppd = PreprocessedData(1)
with self.assertRaises(QiitaDBStatusError):
PreprocessedData.delete(ppd.id)
def test_status(self):
ppd = PreprocessedData(1)
self.assertEqual(ppd.status, 'private')
# Since the status is inferred from the processed data, change the
# status of the processed data so we can check how it changes in the
# preprocessed data
pd = ProcessedData(1)
pd.status = 'public'
self.assertEqual(ppd.status, 'public')
# Check that new preprocessed data has sandbox as status since no
# processed data exists for them
ppd = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="16S")
self.assertEqual(ppd.status, 'sandbox')
def write_demux_files(self, prep_template, generate_hdf5=True):
"""Writes a demux test file to avoid duplication of code"""
fna_fp = join(self.temp_dir, 'seqs.fna')
demux_fp = join(self.temp_dir, 'demux.seqs')
if generate_hdf5:
with open(fna_fp, 'w') as f:
f.write(FASTA_EXAMPLE)
with File(demux_fp, "w") as f:
to_hdf5(fna_fp, f)
else:
with open(demux_fp, 'w') as f:
f.write('')
ppd = PreprocessedData.create(Study(1),
"preprocessed_sequence_illumina_params",
1, [(demux_fp, 6)], prep_template)
return ppd
def test_insert_processed_data_target_gene(self):
fd, fna_fp = mkstemp(suffix='_seqs.fna')
close(fd)
fd, qual_fp = mkstemp(suffix='_seqs.qual')
close(fd)
filepaths = [
(fna_fp, convert_to_id('preprocessed_fasta', 'filepath_type')),
(qual_fp, convert_to_id('preprocessed_fastq', 'filepath_type'))]
preprocessed_data = PreprocessedData.create(
Study(1), "preprocessed_sequence_illumina_params", 1,
filepaths, data_type="18S")
params = ProcessedSortmernaParams(1)
pick_dir = mkdtemp()
path_builder = partial(join, pick_dir)
db_path_builder = partial(join, get_mountpoint('processed_data')[0][1])
# Create a placeholder for the otu table
with open(path_builder('otu_table.biom'), 'w') as f:
f.write('\n')
# Create a placeholder for the directory
mkdir(path_builder('sortmerna_picked_otus'))
# Create the log file
fd, fp = mkstemp(dir=pick_dir, prefix='log_', suffix='.txt')
close(fd)
with open(fp, 'w') as f:
f.write('\n')
_insert_processed_data_target_gene(preprocessed_data, params, pick_dir)
new_id = get_count('qiita.processed_data')
# Check that the files have been copied
db_files = [db_path_builder("%s_otu_table.biom" % new_id),
db_path_builder("%s_sortmerna_picked_otus" % new_id),
db_path_builder("%s_%s" % (new_id, basename(fp)))]
for fp in db_files:
self.assertTrue(exists(fp))
# Check that a new preprocessed data has been created
self.assertTrue(self.conn_handler.execute_fetchone(
"SELECT EXISTS(SELECT * FROM qiita.processed_data WHERE "
"processed_data_id=%s)", (new_id, ))[0])
def test_delete_basic(self):
"""Correctly deletes a preprocessed data"""
# testing regular delete
ppd = PreprocessedData.create(
self.study, self.params_table,
self.params_id, self.filepaths, prep_template=self.prep_template)
PreprocessedData.delete(ppd.id)
# testing that the deleted preprocessed data can't be instantiated
with self.assertRaises(QiitaDBUnknownIDError):
PreprocessedData(ppd.id)
# and for completeness testing that it raises an error if ID
# doesn't exist
with self.assertRaises(QiitaDBUnknownIDError):
PreprocessedData.delete(ppd.id)
# testing that we can not remove cause the preprocessed data != sandbox
with self.assertRaises(QiitaDBStatusError):
PreprocessedData.delete(1)
def test_create_data_type_only(self):
# Check that the returned object has the correct id
new_id = get_count('qiita.preprocessed_data') + 1
obs = PreprocessedData.create(self.study, self.params_table,
self.params_id, self.filepaths,
data_type="18S")
self.assertEqual(obs.id, new_id)
# Check that all the information is initialized correctly
self.assertEqual(obs.processed_data, [])
self.assertEqual(obs.prep_template, [])
self.assertEqual(obs.study, self.study.id)
self.assertEqual(obs.data_type(), "18S")
self.assertEqual(obs.data_type(ret_id=True),
convert_to_id("18S", "data_type"))
self.assertEqual(obs.submitted_to_vamps_status(), "not submitted")
self.assertEqual(obs.processing_status, "not_processed")
self.assertEqual(obs.status, "sandbox")
self.assertEqual(obs.preprocessing_info,
(self.params_table, self.params_id))
def generate_new_study_with_preprocessed_data(self):
"""Creates a new study up to the processed data for testing"""
# ignoring warnings generated when adding templates
simplefilter("ignore")
info = {
"timeseries_type_id": 1,
"metadata_complete": True,
"mixs_compliant": True,
"number_samples_collected": 3,
"number_samples_promised": 3,
"study_alias": "Test EBI",
"study_description": "Study for testing EBI",
"study_abstract": "Study for testing EBI",
"emp_person_id": StudyPerson(2),
"principal_investigator_id": StudyPerson(3),
"lab_person_id": StudyPerson(1)
}
study = Study.create(User('*****@*****.**'), "Test EBI study", [1], info)
metadata_dict = {
'Sample1': {'collection_timestamp': datetime(2015, 6, 1, 7, 0, 0),
'physical_specimen_location': 'location1',
'taxon_id': 9606,
'scientific_name': 'h**o sapiens',
'Description': 'Test Sample 1'},
'Sample2': {'collection_timestamp': datetime(2015, 6, 2, 7, 0, 0),
'physical_specimen_location': 'location1',
'taxon_id': 9606,
'scientific_name': 'h**o sapiens',
'Description': 'Test Sample 2'},
'Sample3': {'collection_timestamp': datetime(2015, 6, 3, 7, 0, 0),
'physical_specimen_location': 'location1',
'taxon_id': 9606,
'scientific_name': 'h**o sapiens',
'Description': 'Test Sample 3'}
}
metadata = pd.DataFrame.from_dict(metadata_dict, orient='index')
SampleTemplate.create(metadata, study)
metadata_dict = {
'Sample1': {'primer': 'GTGCCAGCMGCCGCGGTAA',
'barcode': 'CGTAGAGCTCTC',
'center_name': 'KnightLab',
'platform': 'ILLUMINA',
'instrument_model': 'Illumina MiSeq',
'library_construction_protocol': 'Protocol ABC',
'experiment_design_description': "Random value 1"},
'Sample2': {'primer': 'GTGCCAGCMGCCGCGGTAA',
'barcode': 'CGTAGAGCTCTA',
'center_name': 'KnightLab',
'platform': 'ILLUMINA',
'instrument_model': 'Illumina MiSeq',
'library_construction_protocol': 'Protocol ABC',
'experiment_design_description': "Random value 2"},
'Sample3': {'primer': 'GTGCCAGCMGCCGCGGTAA',
'barcode': 'CGTAGAGCTCTT',
'center_name': 'KnightLab',
'platform': 'ILLUMINA',
'instrument_model': 'Illumina MiSeq',
'library_construction_protocol': 'Protocol ABC',
'experiment_design_description': "Random value 3"},
}
metadata = pd.DataFrame.from_dict(metadata_dict, orient='index')
pt = PrepTemplate.create(metadata, study, "16S", 'Metagenomics')
fna_fp = join(self.temp_dir, 'seqs.fna')
demux_fp = join(self.temp_dir, 'demux.seqs')
with open(fna_fp, 'w') as f:
f.write(FASTA_EXAMPLE_2.format(study.id))
with File(demux_fp, 'w') as f:
to_hdf5(fna_fp, f)
ppd = PreprocessedData.create(
study, "preprocessed_sequence_illumina_params", 1,
[(demux_fp, 6)], pt)
return ppd